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by inlineint 2517 days ago
Looks like an idea for a semi-supervised ensemble method for machine learning:

Prepare two equally sized ensembles of classifiers, let's call them A and B.

1. Train each classifier in ensemble A on labelled data to predict does a picture contains a cat.

2. Take some other unlabelled dataset and collect answers from classifiers from A for each picture from this dataset.

3. Train each classifier in ensemble B to predict average answer of classifiers from A for each picture from the unlabelled dataset.

Then for a picture from the test dataset it would be possible to get answers from ensemble A and from ensemble B and calculate what would be the surprisingly popular answer.

1 comments

Please do this.